Christian G. Graff1
1Division of Imaging and Applied Mathematics, U. S. Food and Drug Administration, Silver Spring, MD, United States
A computational modeling framework has been developed which is able to analyze and compare image quality across different sequences, trajectories and reconstruction techniques. The image quality metrics are based on practical analysis tasks which emulate the complex uses of clinical MR. Using these metrics we show how even complex reconstruction methods such as compressed sensing can be analyzed in a rigorous manner, which is not possible with traditional image quality metrics.